Literature DB >> 21810482

Structure-based drug design to augment hit discovery.

Subha Kalyaanamoorthy1, Yi-Ping Phoebe Chen.   

Abstract

Several technology-based strategies have been developed to address the significance of the two phases of drug discovery: hit identification and lead identification. Structure-based drug design (SBDD), a method that depends on possessing the knowledge of 3D structures of biological targets, is growing swiftly with the development of new technologies for searching potential ways to combat disease. The past decade has evidenced a threefold increase in the amount of software and tools in the online repositories. Herein, we review the in silico strategies and modules applied at the level of hit identification and confer the different challenges with possible solutions in enhancing the success rate of the 'hit-to-lead' phase that could eventually help the progress of SBDD in the drug discovery arena.
Copyright © 2011 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21810482     DOI: 10.1016/j.drudis.2011.07.006

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  51 in total

1.  Thermodynamic Proxies to Compensate for Biases in Drug Discovery Methods.

Authors:  Sean Ekins; Nadia K Litterman; Christopher A Lipinski; Barry A Bunin
Journal:  Pharm Res       Date:  2015-08-27       Impact factor: 4.200

Review 2.  Computational methods in drug discovery.

Authors:  Gregory Sliwoski; Sandeepkumar Kothiwale; Jens Meiler; Edward W Lowe
Journal:  Pharmacol Rev       Date:  2013-12-31       Impact factor: 25.468

3.  Exploration of the Acetylcholinesterase Inhibitory Activity of Some Alkaloids from Amaryllidaceae Family by Molecular Docking In Silico.

Authors:  Willian O Castillo-Ordóñez; Elvira R Tamarozzi; Gabriel M da Silva; Andrés F Aristizabal-Pachón; Elza T Sakamoto-Hojo; Catarina S Takahashi; Silvana Giuliatti
Journal:  Neurochem Res       Date:  2017-05-11       Impact factor: 3.996

4.  Databases of the thiotemplate modular systems (CSDB) and their in silico recombinants (r-CSDB).

Authors:  Janko Diminic; Jurica Zucko; Ida Trninic Ruzic; Ranko Gacesa; Daslav Hranueli; Paul F Long; John Cullum; Antonio Starcevic
Journal:  J Ind Microbiol Biotechnol       Date:  2013-03-16       Impact factor: 3.346

5.  A rational free energy-based approach to understanding and targeting disease-causing missense mutations.

Authors:  Zhe Zhang; Shawn Witham; Marharita Petukh; Gautier Moroy; Maria Miteva; Yoshihiko Ikeguchi; Emil Alexov
Journal:  J Am Med Inform Assoc       Date:  2013-02-13       Impact factor: 4.497

6.  Perspective: Markov models for long-timescale biomolecular dynamics.

Authors:  C R Schwantes; R T McGibbon; V S Pande
Journal:  J Chem Phys       Date:  2014-09-07       Impact factor: 3.488

7.  In silico investigation of lavandulyl flavonoids for the development of potent fatty acid synthase-inhibitory prototypes.

Authors:  Joonseok Oh; Haining Liu; Hyun Bong Park; Daneel Ferreira; Gil-Saeng Jeong; Mark T Hamann; Robert J Doerksen; MinKyun Na
Journal:  Biochim Biophys Acta Gen Subj       Date:  2016-08-13       Impact factor: 3.770

Review 8.  Bioinformatics and variability in drug response: a protein structural perspective.

Authors:  Jennifer L Lahti; Grace W Tang; Emidio Capriotti; Tianyun Liu; Russ B Altman
Journal:  J R Soc Interface       Date:  2012-05-02       Impact factor: 4.118

Review 9.  Therapeutic Potential of Spirooxindoles as Antiviral Agents.

Authors:  Na Ye; Haiying Chen; Eric A Wold; Pei-Yong Shi; Jia Zhou
Journal:  ACS Infect Dis       Date:  2016-05-05       Impact factor: 5.084

10.  Integrating virtual and biochemical screening for protein tyrosine phosphatase inhibitor discovery.

Authors:  Katie R Martin; Pooja Narang; José L Medina-Franco; Nathalie Meurice; Jeffrey P MacKeigan
Journal:  Methods       Date:  2013-08-20       Impact factor: 3.608

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.